Add to ORKGThe Rao-Wu bootstrap variance estimation method is frequently used at Statistics Canada. It is simple to implement, the same formula applies to all estimators, including non-smooth statistics, and it enables the analysts to use the design-based approach. The method assumes primary sampling units are selected with replacement or the first-stage sampling fractions are negligible. We examine the properties of the Rao-Wu bootstrap variance estimator for a two-stage design and a variety of scenarios: different sampling methods, varying sampling fractions, several variables and estimators. We also compare these properties with those of the analytical variance estimators
Consider a finite population from which the stratified sample with simple random sample without repl...
Estimating standard errors of estimated variance components has long been a challen-ging task in gen...
Using the Canadian Workplace and Employee Survey (WES), three variance estimation methods for weight...
The bootstrap method is increasingly used to estimate the variance of estimates obtained from comple...
In complex survey sampling every population unit is assigned a specific probability to be included ...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
This article provides general procedures for obtaining unbiased estimates of variance components for...
In large multipurpose surveys, it is common to select the sample systematically proportional to some...
Abstract This paper presents a comparison of the nonparametric and parametric bootstrap methods, whe...
The bootstrap approach to statistical inference is described in Efron (1982). The method has wide ap...
Variance estimation techniques for nonlinear statistics, such as ratios and regression and correlati...
Whether survey data are being used for estimating descriptive statistics about the population from w...
The problem of the estimation of the design-variance and the design-MSE of different estimators and ...
Several features of sample surveys generally render inapplicable the st and ard explicit forms of va...
Consider a finite population from which the stratified sample with simple random sample without repl...
Estimating standard errors of estimated variance components has long been a challen-ging task in gen...
Using the Canadian Workplace and Employee Survey (WES), three variance estimation methods for weight...
The bootstrap method is increasingly used to estimate the variance of estimates obtained from comple...
In complex survey sampling every population unit is assigned a specific probability to be included ...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
This article provides general procedures for obtaining unbiased estimates of variance components for...
In large multipurpose surveys, it is common to select the sample systematically proportional to some...
Abstract This paper presents a comparison of the nonparametric and parametric bootstrap methods, whe...
The bootstrap approach to statistical inference is described in Efron (1982). The method has wide ap...
Variance estimation techniques for nonlinear statistics, such as ratios and regression and correlati...
Whether survey data are being used for estimating descriptive statistics about the population from w...
The problem of the estimation of the design-variance and the design-MSE of different estimators and ...
Several features of sample surveys generally render inapplicable the st and ard explicit forms of va...
Consider a finite population from which the stratified sample with simple random sample without repl...
Estimating standard errors of estimated variance components has long been a challen-ging task in gen...
Using the Canadian Workplace and Employee Survey (WES), three variance estimation methods for weight...